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Guardrisk is the undisputed market leader in cell captive insurance and risk solutions. We are renowned for our innovative approach to cell captive structures and other alternative risk transfer solutions for our clients. Guardrisk offers clients custom designed cover and is registered in South Africa as an insurer for all statutory classes of non-life and life insurance business. Role Purpose The Data Engineer – Data Acquisition at Guardrisk is a hands-on integration and data enablement role responsible for ensuring that external data providers (cells, binder holders, system providers, administrators, and partners) deliver complete, accurate, timely, and technically compliant data that Guardrisk can reliably ingest and process. The role exists to design, implement, and operationalise external data ingestion pipelines , with a primary focus on premium bordereaux , and secondary responsibility for master and transactional data exchanged with third parties. This role works directly with external parties , engaging them on data structures, formats, validation rules, delivery mechanisms, and remediation of issues. It partners closely with the Data Architect (to align to target architecture and data models), Data Analysts (to ensure analytical usability), and Data Stewards (to ensure operational data quality once data is live). The role is delivery-oriented and externally facing , bridging business requirements, technical standards, and partner capabilities to ensure Guardrisk can confidently process and rely on third‑party data. Duties and Responsibilities External Data Acquisition & Integration (Primary Accountability) Design, build, and maintain data ingestion pipelines for external data sources, with a primary focus on: Premium bordereaux (BDX) Policy and transactional feeds Supporting master data where required Implement ingestion patterns aligned to Guardrisk’s data architecture (batch, file-based, API, secure transfer). Ensure external data conforms to agreed: Data models Schemas Validation and reconciliation rules Delivery frequency and cut-offs Enable scalable and repeatable onboarding of new external data providers External Partner Engagement & Enablement Act as the technical data interface between Guardrisk and external providers. Engage directly with: Cells Binder holders Administrators System providers Support partners by: Explaining Guardrisk data requirements and standards Assisting with mapping, formatting, and transformation logic Advising on delivery mechanisms and error handling Drive remediation where partner data does not meet required standards Travel to partner and provide onsite support Premium BDX Enablement & Control Implement robust ingestion and validation of premium bordereaux , including: Structural validation Completeness checks Reconciliation against expected volumes and values Ensure BDX data is fit for: Finance and premium recognition Underwriting performance analysis Regulatory and internal reporting Work with Data Analysts and Finance to resolve discrepancies early in the pipeline Data Quality & Issue Resolution (Engineering Perspective) Build and Support automated validation and control checks into ingestion pipelines. Support the Data Validator and the rollout in the external data provider space. Partner with Data Stewards when operational data quality issues are detected. Perform root cause analysis across: Source systems Partner delivery processes Ingestion and transformation logic Implement durable fixes rather than manual workarounds Alignment with Data Architecture & Analytics Work closely with the Data Architect to ensure: External data aligns to Guardrisk canonical models Integration patterns support the target architecture Collaborate with Data Analysts to ensure: External data is usable for analytical and reporting purposes Key business metrics can be reliably derived Ensure ingestion design balances technical correctness and business usability Documentation & Data Contracts Maintain practical technical documentation for external data integrations, including: Data schemas Mapping specifications Validation rules Known constraints or caveats Support the definition and enforcement of data contracts with external providers. Qualifications Bachelor’s Degree in Computer Science, Information Systems, Engineering, or related field. Strong emphasis on practical data engineering experience over theoretical qualifications. Experience 5+ years’ experience as a data engineer , with demonstrable focus on: External data ingestion and integration File- and API-based data exchange Data validation and reconciliation Strong experience working with: Bordereaux or high‑volume transactional data Financial or insurance datasets Proven experience engaging directly with external data providers . Solid exposure to Microsoft Azure data technologies (e.g. Azure Data Factory, Synapse, Databricks, SQL). Insurance domain experience strongly preferred, especially where data impacts: Premium processing Finance Reporting and regulatory submissions Soft Skills Strong analytical and problem‑solving ability, with a focus on diagnosing data designs, patterns and solutions under operational pressure High attention to detail, particularly when working with data used in critical business processes Clear, confident communicator able to explain data issues and solutions in business‑friendly language Comfortable working across business and technical teams to drive resolution Accountable and outcomes‑focused, with a bias toward action rather than escalation Should you not hear from us within 21 days, kindly consider your application unsuccessful.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.